The present invention relates to image alignment, and more particularly to image alignment with global translation and linear stretch which is detected and corrected.
Accurate spatial alignment of digital images is of fundamental importance to many applications. xe2x80x9cComputer Image Processing and Recognitionxe2x80x9d by Ernest Hall, Academic Press 1979, pp. 480-484, describes a basic correlation method for template matching which may be used for image alignment. xe2x80x9cThe Phase Correlation Image Alignment Methodxe2x80x9d by C. D. Kuglin et al, Proceedings of the IEEE 1975 Internal Conference on Cybernetics and Society, September 1975, pp. 163-165, describes a variant of the basic correlator that uses phase information. These methods are appropriate for global translation, such as shown in FIGS. 1A and 1B, and can be very accurate. However for digital images that also are distorted with a linear stretch, as shown in FIGS. 2A and 2B, these correlation methods alone are not capable of handling such a complex model.
A more general approach is taken by James R. Muller et al., xe2x80x9cAdaptive-Complexity Registration of Imagesxe2x80x9d, Technical Report 941, University of Rochester, May 1994. The model complexity for local regions may be adaptively expanded to include global translation as well as higher order models, such as linear (affine) to quadratic. However the sizes of the subregions must be substantial to avoid aliasing problems so that, when stitched together, the boundaries between subregions usually pose a problem. In addition there is no global stretch parameter derived.
What is desired is an image alignment method that compensates both for global translation and linear stretch.
Accordingly the present invention provides an image alignment method that compensates for global translation and linear stretch. Using left, center and right correlation blocks, translation parameters are determined between a reference image and a corresponding distorted test image. Based upon the differences between the translation parameters for the blocks, linear stretch is detected and a rough estimate of a stretch factor is determined. The estimated stretch factor is fine tuned by centering the reference image relative to the distorted test image and then stretching the reference image linearly using a linear interpolation operation starting with the estimated stretch factor until the two images overlap as closely as possible, the final stretch factor being that which results in the closest overlap. Then the distorted test image is unshrunk using the refined stretch factor and translated so that the distorted test image is aligned with the reference image for picture quality analysis, for example.